#Spacenet 2 install#
#Spacenet 2 code#

**To win the Early Incentive your solution must be the first to reach a threshold of 400,000 for the average F-score of all the cities. Here is the prize list for this particular Marathon Match: Prize Not only are Topcoder members using their algorithm skills to improve the way we use satellite imagery, but they are also making bank.

All winning solutions must be submitted as docker containers with all preprocessing and post-processing steps.

Organizations can participate but will not be eligible for prize money.

#Spacenet 2 code#

Source code and algorithm description of round 1 winners is available.Usage of external data and pretrained models are explicitly allowed.The length of the competition is longer (2 months).The quality of the building footprint annotations has been improved.There are multiple new imagery formats (i.e., PAN, MUL, RGB-PanSharpen, MUL-PanSharpen).There is much more data, featuring 4 cities.The most important differences are the following: Most of the problem statement is identical to the specification used in the first challenge. This contest is the second edition of the SpaceNet building footprint detection challenge. Moving toward more accurate, fully automated extraction of buildings will help bring innovation to computer vision methodologies applied to high-resolution satellite imagery, and ultimately help create better maps where they are most needed. In this challenge, competitors are tasked with finding automated methods for extracting map-ready building footprints from high-resolution satellite imagery. This popular Marathon Match - sponsored by CosmiQ Works, DigitalGlobe, and NVIDIA - is challenging the Topcoder Community to develop automated methods for extracting building footprints from high-resolution satellite imagery.

#Spacenet 2 install#

This, although a crapy solution (Do I really need to create a new env, install tf and pytorch and lot of dependencies, install GDAL, etc to open an image?) at this point I am Ok with whatever works.If the SpaceNet Challenge Round 2 were a basketball game, we would just be starting the fourth quarter. Solaris 0.0.2 depends on torchvision>=0.3.0Īnd it was a NEW environment without tf nor pytorch installed. Solaris 0.0.3 depends on torchvision>=0.3.0 Solaris 0.1.0 depends on torchvision>=0.3.0 Solaris 0.1.1 depends on torchvision>=0.3.0 Solaris 0.1.2 depends on torchvision>=0.3.0 Solaris 0.1.3 depends on torchvision>=0.3.0 Solaris 0.2.0 depends on torchvision>=0.3.0 Solaris 0.2.1 depends on torchvision>=0.4.2 As the documentation says I need to install GDAL so at this point why not? sudo apt-get install libgdal-dev but then I still got errors like: ERROR: Cannot install solaris=0.0.1, solaris=0.0.2, solaris=0.0.3, solaris=0.1.0, solaris=0.1.1, solaris=0.1.2, solaris=0.1.3, solaris=0.2.0, solaris=0.2.1, solaris=0.2.2, solaris=0.3.0 and solaris=0.4.0 because these package versions have conflicting dependencies. I tried creating a new environment to install it from scratch. I tried installing it but it requires TensorFlow version to be tf v1.13 and I already have version 2 and I need it. I've seen that this code uses a library called solaris. Has someone already succeeded in opening this library?

skimage: Tiff: data type not supported: 532.

Matplotlib: cannot identify image file ''.

OpenCV: [ global /io/opencv/modules/imgcodecs/src/grfmt_tiff.cpp (462) readData OpenCV TIFF: TIFFRGBAImageOK: Sorry, can not handle images with 32-bit samples.

I tried OpenCV, matplotlib, PIL and skimage. Now the issue arises when I use python to open the.

I downloaded the dataset successfully using aws. The SpaceNet Dataset is hosted as an Amazon Web Services (AWS) Public Dataset.It contains 67,000 square km of very high-resolution imagery, >11M building footprints, and 20,000 km of road labels to ensure that there is adequate open source data available for geospatial machine learning research. I particularly need the SAR-SLC data as I want to have the raw complex-valued dataset. So I am trying to access the open-source SAR dataset SpaceNet 6: Expanded Dataset.